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The ability of the developed non-LTE inversion tool to retrieve stratospheric NO abundances is demonstrated by retrieval simulations.
The degree of oil saturation has been estimated from velocity measurements of unconsolidated sediments at a laboratory scale using a petrophysical model and artificial neural network (ANN) as an inversion tool.
Instead of using nonlinear stochastic algorithms like the simulated annealing (SA) technique that we optimized in previous studies to image permittivity distributions of granular or solid materials as well as real oil-gas or two-phase flows in 2D cylindrical vessel configurations, we propose here a new ECT inversion tool to image permittivities in a 3D cylindrical configuration.
The characterization of uncertainty is crucial to the effective use of a model as an inversion tool.
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This integrative approach can potentially lead to significant savings in time and manpower as one is able to condition large prior geology models to dynamic data with fast streamline simulation and travel time inversion tools.
Mathematical models of natural processes can be used as inversion tools to predict unobserved properties from measured quantities.
Frequently, models are used as inversion tools to infer properties of a system that are difficult to measure directly from observations that can be made more easily.
We compare the runtimes and precisions of CCMpred with two other pseudo-likelihood maximization (PLM -based tools, PLM -basedmDCA-symmetools3, plmDCA-asymmetric 1) and GREMLIN (version 2.01), and with the covariance matrix inversion-based tool PSICOV.
A moment tensor inversion is a powerful tool for extracting source information from seismic and geodetic observations.
These results show that the EOF-based inversion provides a new tool for the analysis of MARSIS ionograms.
Amplitude variation with offset and azimuth (AVOA) inversion is a powerful tool used to predict the fluid and fracture information by utilizing the observable seismic reflection amplitudes.
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